Upload app.py

app.py

@@ -1,19 +1,24 @@
 import gradio as gr
 import numpy as np
 from transformers import pipeline
-
+from model import DepressionClassifier
 import hopsworks
 import joblib
+import torch
+class_names = ['Not Depressed', 'Depressed']
+model = DepressionClassifier(len(class_names), 'bert-base-cased')
+model.load_state_dict(torch.load("liangc40/sentimental_analysis/model.pt"))
+model.eval()
 #pipe = pipeline(model="liangc40/sentimental_analysis")
 
-project = hopsworks.login(project='liangc40')
-fs = project.get_feature_store()
+#project = hopsworks.login(project='liangc40')
+#fs = project.get_feature_store()
 
 
-mr = project.get_model_registry()
-model = mr.get_model("sentimental_analysis_model", version=3)
-model_dir = model.download()
-model = joblib.load(model_dir + "/sentimental_analysis_model.pkl")
+#mr = project.get_model_registry()
+#model = mr.get_model("sentimental_analysis_model", version=1)
+#model_dir = model.download()
+#model = joblib.load(model_dir + "/sentimental_analysis_model.pkl")
 
 def analyse(text):
     label = pipe(text)